Background: Several studies have shown a substantial impact of Rotavirus (RV) vaccination on the burden of RV and all-cause acute gastroenteritis (AGE). However, the results of most impact studies could be confused by a dynamic and complex space-time process. Therefore, there is a need to analyse the impact of RV vaccination on RV and AGE hospitalisations in a space-time framework to detect geographical-time patterns while avoiding the potential confusion caused by population inequalities in the impact estimations.
Methods: A retrospective population-based study using real-world data from the Valencia Region was performed among children aged less than 3 years old in the period 2005-2016. A Bayesian spatio-temporal model was constructed to analyse RV and AGE hospitalisations and to estimate the vaccination impact measured in averted hospitalisations.
Results: We found important spatio-temporal patterns in RV and AGE hospitalisations, RV vaccination coverage and in their associated adverted hospitalisations. Overall, ~ 1866 hospital admissions for RV were averted by RV vaccination during 2007-2016. Despite the low-medium vaccine coverage (~ 50%) in 2015-2016, relevant 36 and 20% reductions were estimated in RV and AGE hospitalisations respectively.
Conclusions: The introduction of the RV vaccines has substantially reduced the number of RV hospitalisations, averting ~ 1866 admissions during 2007-2016 which were space and time dependent. This study improves the methodologies commonly used to estimate the RV vaccine impact and their interpretation.
Keywords: Bayesian model; Real-world data; Rotavirus; Spatio-temporal; Vaccine impact.